Seungkwon Beack

A noise robust audio fingerprint extraction technique for mobile devices using gradient histograms

Audio fingerprinting technology is commonly used in the field of automatic content recognition (ACR). Although various audio fingerprinting techniques have previously been proposed, we propose an advanced landmark extraction technique built on gradient-based features. With the widespread use of smart phones, a large number of audio fingerprinting applications are currently running on mobile phones in outdoor environments. As a result, these audio fingerprinting systems suffer from noise interference. To overcome this problem, we propose a novel scheme to effectively extract salient features and identify an audio signal from them. Test results show that our proposed approach can more accurately identify an audio signal in a noisy environment.

Acoustic data transmission by extension on the time domain approach

The main goal of acoustic data transmission is to deliver data by overcoming acoustic channel distortion. This paper presents a data transmission method that modifies the amplitude of the time domain audio signal imperceptibly. The main advantage of the proposed method is that the synchronization process can be conducted simultaneously while data is being extracted at the receiver side. The evaluation results show that the proposed method successfully overcomes indoor acoustic channel distortion and delivers data.